Long-Term Effects of Ranirestat (AS-3201) on Peripheral Nerve Function in Patients With Diabetic Sensorimotor Polyneuropathy
Bibliographic record
Abstract
OBJECTIVES: We aimed to determine whether ranirestat, an aldose reductase inhibitor, maintains the improved nerve function observed in patients with diabetic sensorimotor polyneuropathy (DSP) after completing a 12-week nerve biopsy study. RESEARCH DESIGN AND METHODS: Patients with mild to moderate DSP, as determined by the presence of sural nerve responses, were enrolled in a double-blind, placebo-controlled biopsy trial and randomized to placebo or 5 or 20 mg/day ranirestat for 12 weeks. Patients completing this biopsy study were offered a 48-week extension at the same ranirestat dose or at 5 mg/day ranirestat if they were originally treated with placebo. Electrophysiological tests, the Toronto Clinical Neuropathy Score, and vibration perception thresholds (VPTs) were performed at entry and at 12 (end of the biopsy study) and 60 (end of the 48-week extension) weeks. RESULTS: Peroneal motor nerve conduction velocity (NCV) improved in the 20-mg/day group following 60 weeks of treatment. Sural and median sensory NCV improved after both 12 and 60 weeks of treatment with 20 mg/day. VPT improved after 60 weeks of treatment with 20 mg/day. Ranirestat was well tolerated with no difference in adverse events between the 5- and 20-mg/day groups. CONCLUSIONS: Twenty milligrams ranirestat per day improves NCV and VPT following 60 weeks of administration. The improved sensory nerve function observed after 12 weeks of therapy was maintained at 60 weeks, and improved motor nerve function was observed at 60 weeks.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".